Tencent Data Scientist Interview Questions
The questions to prepare for a Tencent Data Scientist interview. Questions from real interview reports rank first. Updated daily.
Compute daily active users and a 7-day rolling average using a CTE, distinct counts, and window functions.
TencentCompare weekly active users by Tencent region and product version to identify the largest week-over-week declines.
TencentRank Dayforce users by quarterly engagement and return the top 10% using aggregation and NTILE().
Dayforce
Lattice
Condé NastExplain how bagging and boosting differ in ensemble training, error reduction, and model behavior.
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Interpret an experiment where the short-term primary metric improves but long-term retention worsens, and decide whether to ship.
TencentExplain how to reduce memory usage and stabilize a Pandas-based batch pipeline that is failing on larger inputs.
TencentExplain how to test whether an observed experiment lift is real using hypothesis testing, p-values, and confidence intervals.
TencentDefine a success metric for a new feature that captures real user value, not just raw usage.
TencentPick the right metrics to evaluate a machine learning model and explain why they fit the problem.
TencentAnalyze where users drop off in a product funnel and identify the biggest conversion leak.
Tencent